Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use luthfi507/emotion-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use luthfi507/emotion-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="luthfi507/emotion-classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("luthfi507/emotion-classification") model = AutoModelForImageClassification.from_pretrained("luthfi507/emotion-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71f9d44baf0f1fafbc7780b27f130553717c79ac7a5ed9fc4faeeb874dacbf19
- Size of remote file:
- 5.11 kB
- SHA256:
- e475b08d7d31e610e81860a7173d5f5d4c7081b54d483503f91314bc3be9ea4b
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